A new approach for solving multi-objective transportation problems

Nomani, Mohammad Asim; Ali, Irfan; Ahmed, Aquil

doi:10.1080/17509653.2016.1172994

Cited by 18 publications

(16 citation statements)

References 19 publications

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“…and conditions (18)- (22), and (24). where: L p is a metric for optimal solution, F(x) * j is the ideal value of criterion j (in the case of minimization this is the minimal value of criterion, F(x) * * j is the anti-ideal point for the j-th objective (in the case of minimization this is the maximal value of the solutions-max j F(x) j , p is a parameter that is used to present the attitude of the decision-maker with respect to compensation between deviations; p = 1 is the so-called street-block distance, or Manhattan distance; p = 2, it is represents the Euclidean distance; p = ∞, it is Tchebyshev distance, and correspond to min-max problem.…”

Section: Step 4: Multi-objective Optimizationmentioning

confidence: 99%

“…Fuzzy mathematical programing was applied to solve the multi-objective problem. In [22], a new multi-objective approach with examples of two and three objectives was studied.…”

Section: Introductionmentioning

confidence: 99%

“…It may be concluded that the following problems were studied: railway route planning, design of transfer stations, supply chain planning, passenger train service, stop planning, train schedule planning, train routing, and transport planning. Most authors consider the main criteria as the operating cost and time travel, which has a great importance for developing the transport plan of the trains, [11,15,19,[21][22][23][24]29]. Some authors also investigated the criteria of transfer interval time [7], delayed times [13], social risk [17], transport risk [18], total energy consumption [20], damage cost [22], functionality and upgradeability, number of overtaking [25], compliance with standards [26], and the pollution factor [29].…”

Section: Introductionmentioning

confidence: 99%

“…The authors used a multi-criteria approach such as AHP method [6] or MOO. To summarize, the following multi-objective methods that were applied: epsilon-constraint method [9,10,15,25,27], lexicographical approach [23], fuzzy approach [11,16,21], WSM [12,17,19,22], genetic algorithm [13,14,19,20], and hybrid method WSM and epsilon-constraint [26]. Epsilon-constraint method and WSM were used most by the authors.…”

Section: Introductionmentioning

confidence: 99%

“…To determine the consistency of the experts' assessment in the study the Spearman Rank correlation coefficient is proposed, Ref. [22].…”

mentioning

confidence: 99%

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An Integrated Multi-Criteria and Multi-Objective Optimization Approach for Establishing the Transport Plan of Intercity Trains

Stoilova

2020

Sustainability

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The development of the transport plan must take into account various criteria impacting the transport process. The main objective of the study is to propose an integrated approach to determine the transport plan of passenger trains. The methodology consists of five steps. In the first step, the criteria for optimization of the transport plan were defined. In the second step, variants of the transport plan were formulated. In the third step, the weights of the criteria are determined by applying the step-wise weight assessment ratio analysis method (SWARA) multi-criteria method. The multi-objective optimization was conducted in the fourth step. The following multi-objective optimization approaches were used and compared: weighted sum method (WSM), compromise programming method (CP), and the epsilon–constraint method (EC). The study proposes a modified epsilon–constraint method (MEC) by applying normalization of each objective function according to the maximal value of the solution by individual optimization for each objective function, and hybrid methods: hybrid WSM and EC, hybrid WSM and MEC, hybrid CP and EC, and Hybrid CP and MEC. The impact of the variation of passenger flows on the choice of an optimal transport plan was studied in the fifth step. The Laplace’s criterion, Hurwitz’s criterion, and Savage’s criterion were applied to come to a decision. The approbation of the methodology was demonstrated through the case study of Bulgaria’s railway network. Suitable variant of transport plan is proposed.

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Section: Step 4: Multi-objective Optimizationmentioning

confidence: 99%

“…Fuzzy mathematical programing was applied to solve the multi-objective problem. In [22], a new multi-objective approach with examples of two and three objectives was studied.…”

Section: Introductionmentioning

confidence: 99%